Hadoop Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Hadoop Data Engineer on a contract basis, requiring 5+ years of experience in Databricks, Azure, Scala, and Hadoop. The position is onsite in "Boston, MA/Quincy, MA/Princeton, NJ" with a competitive pay rate.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
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🗓️ - Date discovered
August 16, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Unknown
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🔒 - Security clearance
Unknown
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📍 - Location detailed
Boston, MA
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🧠 - Skills detailed
#"ACID (Atomicity #Consistency #Isolation #Durability)" #Data Manipulation #Cloud #Delta Lake #Databricks #Data Warehouse #Data Science #Data Modeling #Azure Databricks #Agile #Azure #JSON (JavaScript Object Notation) #Sqoop (Apache Sqoop) #Data Lake #Datasets #ADF (Azure Data Factory) #Scrum #Azure Event Hubs #Azure Synapse Analytics #Big Data #Snowflake #Data Governance #Scala #Synapse #Spark (Apache Spark) #Azure Data Factory #Data Processing #Deployment #Data Quality #Hadoop #YARN (Yet Another Resource Negotiator) #Azure cloud #"ETL (Extract #Transform #Load)" #Apache Spark #Data Engineering #Distributed Computing #Data Pipeline #Security #HDFS (Hadoop Distributed File System) #Code Reviews #Programming #SQL (Structured Query Language)
Role description
le: Big Data Engineer – Databricks, Azure, Scala, Hadoop
Location: Boston, MA/Quincy, MA/Princeton, NJ(Onsite)\_Local Preferred
Job Type: Contract
Job Summary
We are seeking a highly skilled Data Engineer with strong expertise in Databricks, Azure, Scala, and Hadoop to design, build, and optimize large-scale data pipelines and analytics solutions. The ideal candidate will have deep experience in big data technologies, cloud platforms, and distributed computing, and will work closely with data scientists, analysts, and business teams to deliver reliable and high-performing data solutions.
Key Responsibilities:
Design, develop, and maintain ETL/ELT pipelines in Databricks using Scala and Spark.
Build and optimize data processing workflows for structured and unstructured data.
Implement solutions using Azure services (Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Azure Event Hubs, Azure Databricks).
Work with Hadoop ecosystem (HDFS, Hive, YARN, Oozie, Sqoop) for big data processing.
Design and maintain data lake and data warehouse architectures.
Use Delta Lake for ACID transactions and scalable data pipelines.
Collaborate with cross-functional teams to understand data requirements and deliver analytics-ready datasets.
Ensure data quality, governance, and security across all environments.
Optimize Spark jobs for performance and cost efficiency.
Participate in code reviews, CI/CD deployments, and Agile/Scrum processes.
Required Skills & Experience
5+ years of experience as a Data Engineer or Big Data Developer.
Strong hands-on experience with Databricks and Apache Spark.
Proficiency in Scala programming for big data processing.
Experience with Azure cloud services for data engineering.
Knowledge of Hadoop ecosystem tools and frameworks.
Strong SQL skills for data manipulation and transformation.
Familiarity with data formats (Parquet, ORC, Avro, JSON, CSV).
Experience in data modeling (dimensional, star schema, snowflake).
Understanding of data governance, quality, and security best practices.
Excellent problem-solving skills and ability to work in fast-paced environments.
le: Big Data Engineer – Databricks, Azure, Scala, Hadoop
Location: Boston, MA/Quincy, MA/Princeton, NJ(Onsite)\_Local Preferred
Job Type: Contract
Job Summary
We are seeking a highly skilled Data Engineer with strong expertise in Databricks, Azure, Scala, and Hadoop to design, build, and optimize large-scale data pipelines and analytics solutions. The ideal candidate will have deep experience in big data technologies, cloud platforms, and distributed computing, and will work closely with data scientists, analysts, and business teams to deliver reliable and high-performing data solutions.
Key Responsibilities:
Design, develop, and maintain ETL/ELT pipelines in Databricks using Scala and Spark.
Build and optimize data processing workflows for structured and unstructured data.
Implement solutions using Azure services (Azure Data Lake, Azure Synapse Analytics, Azure Data Factory, Azure Event Hubs, Azure Databricks).
Work with Hadoop ecosystem (HDFS, Hive, YARN, Oozie, Sqoop) for big data processing.
Design and maintain data lake and data warehouse architectures.
Use Delta Lake for ACID transactions and scalable data pipelines.
Collaborate with cross-functional teams to understand data requirements and deliver analytics-ready datasets.
Ensure data quality, governance, and security across all environments.
Optimize Spark jobs for performance and cost efficiency.
Participate in code reviews, CI/CD deployments, and Agile/Scrum processes.
Required Skills & Experience
5+ years of experience as a Data Engineer or Big Data Developer.
Strong hands-on experience with Databricks and Apache Spark.
Proficiency in Scala programming for big data processing.
Experience with Azure cloud services for data engineering.
Knowledge of Hadoop ecosystem tools and frameworks.
Strong SQL skills for data manipulation and transformation.
Familiarity with data formats (Parquet, ORC, Avro, JSON, CSV).
Experience in data modeling (dimensional, star schema, snowflake).
Understanding of data governance, quality, and security best practices.
Excellent problem-solving skills and ability to work in fast-paced environments.
